https://github.com/igorjakus/neurohackathon

Epileptic Seizure Detection System for NeuroHackathon 2024 engineered with Hubert Berlicki, Kyrylo Goroshenko and Lidia Podoluk
https://github.com/igorjakus/neurohackathon

bci brain-computer-interface hackathon healthcare machine-learning neuroscience seizure-detection seizure-prediction

Last synced: about 1 month ago
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Epileptic Seizure Detection System for NeuroHackathon 2024 engineered with Hubert Berlicki, Kyrylo Goroshenko and Lidia Podoluk

• Host: GitHub
• URL: https://github.com/igorjakus/neurohackathon
• Owner: igorjakus
• Created: 2024-11-16T12:03:18.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2025-01-07T12:01:06.000Z (about 1 month ago)
• Last Synced: 2025-01-07T12:31:51.310Z (about 1 month ago)
• Topics: bci, brain-computer-interface, hackathon, healthcare, machine-learning, neuroscience, seizure-detection, seizure-prediction
• Language: Jupyter Notebook
• Homepage:
• Size: 11.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# BCI-Based Epileptic Seizure Detection and Warning System

## Idea

This project is a Brain-Computer Interface (BCI) system designed to detect and warn users of the potential risk of epileptic seizures. Using advanced signal processing techniques and machine learning algorithms, the system analyzes EEG (Electroencephalography) data to identify patterns associated with seizure onset. The goal is to provide timely alerts, enabling individuals with epilepsy and their relatives to take preventive measures and improve their quality of life.

## Features

- Predicts and detects epileptic seizures using real-time EEG data with a BCI.

- Provides timely alerts to users or their close ones.

- Achieved 98% accuracy with minimal false negatives.

- Utilized SVM, with additional experiments using DNN, KNN, and KMeans models.

#### [Dataset, paper](https://www.ukbonn.de/epileptologie/arbeitsgruppen/ag-lehnertz-neurophysik/downloads/)